Evidences suggested that use levels of inorganic fertilizers are below the recommended rates in maize production. It is, therefore, necessary to investigate the reasons behind the failure to adopt the recommended rates of these fertilizers on maize production. This study analyzed determinants of intensity of adoption using a survey data collected from 383 randomly selected maize producing households. For this purpose, a two-limit Tobit model was applied. The econometric result revealed that variation in districts, family size, membership to cooperatives, distance to FTC, and livestock holding significantly affected smallholders’ intensity of adoption of DAP in maize production. On the other side, variation in district, farming experience, farm size, membership to cooperatives, dependency ratio, and annual income significantly determined intensity of adoption of Urea. It is, therefore, necessary to give due emphasis to the indicated determinants in order to assist maize producing farmers by boosting maize productivity.

A study was conducted to analyze factors influencing adoption of wheat technology packages by smallholder farmers in Gurawa, Meta and Habro districts in eastern Ethiopia. The analysis was based on a household survey data collected from 136 randomly selected households. A Two-limit Tobit model was used to elucidate factors affecting adoption of technology packages measured based on an index derived from five components of wheat technologies which included row planting, pesticide application, use of improved varieties, and application of inorganic fertilizers, namely, Diammonium Phosphate (DAP) and Urea. Among the variables included in the model, variation in district, gender, age of the household head, education status of the household head, farm size, distance to market, distance to FTC (Farmers' Training Centers), cooperative membership, dependency ratio, and annual income of the households were found to significantly affect the adoption of wheat technology packages. Policy makers, planners and development practitioners should give due attention to these determinants to support smallholder farmers in wheat production and enhance gains derived from it.

Evidences suggested that use levels of inorganic fertilizers in potato production in Ethiopia are below the recommended rates. This study is aimed at accessing factors contributing to this. The study utilized data collected from 171 randomly selected potato producing households. A two-limit Tobit model result revealed that variation in districts, access to irrigation, frequency of extension contact, and livestock holding significantly affected intensity of adoption of both DAP and Urea in potato production. In addition, access to credit and annual income significantly determined adoption intensity of DAP. It is therefore, essential to give due emphasis to these determinants in supporting smallholder farmers in order to enhance potato productivity.

Production of wheat by smallholder farmers in Ethiopia contributes a significant share to the agricultural production of the country. However, the actual productivity of the crop has been far below its potential. Varied levels of technology adoption are often observed among smallholder farmers producing the crop. For enhanced dissemination of technology packages and improving wheat productivity, it is vital to elucidate socio-economic factors that are behind disparity in technology adaption among smallholder farmers. Therefore, this study was conducted to analyse the socioeconomic, institutional, and other pertinent variables that determine the existing disparity observed among smallholder farmers in terms of adopting wheat production technology packages in Gurawa and Meta districts of eastern Ethiopia. The study utilized survey data collected from 124 randomly selected wheat households producing wheat. For this purpose, an ordered logit model was applied. The econometric results revealed that age of the household head, membership in cooperative institutions, and household annual income significantly and positively explained the disparity observed in adoption of wheat production technology packages. Conversely, gender of household head (sex), farming experiences, number of plots owned, and frequency of contacts with extension agents explained the disparity significantly, but negatively. It could be concluded that development practitioners, planners, and policy makers should give due considerations to the aforementioned socio-economic and institutional factors when designing dissemination of wheat production technology packages for adoption by farmers.

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